Discovering the key symptoms for identifying patterns in functional dyspepsia patients: A doctor's decision and machine learning by Da-Eun Yoon, Heeyoung Moon, In-Seon Lee, Younbyoung Chae

“…Implicit importance was assessed by feature importance from the random forest classification models, which classify the three pattern for general differentiation and perform binary classification for specific types. …”
Get full text

Cross-User Electromyography Pattern Recognition Based on a Novel Spatial-Temporal Graph Convolutional Network by Mengjuan Xu, Xiang Chen, Yuwen Ruan, Xu Zhang

“…With the goal of promoting the development of myoelectric control technology, this paper focuses on exploring graph neural network (GNN) based robust electromyography (EMG) pattern recognition solutions. Given that high-density surface EMG (HD-sEMG) signal contains rich temporal and spatial information, the multi-view spatial-temporal graph convolutional network (MSTGCN)is adopted as the basic classifier, and a feature extraction convolutional neural network (CNN) module is designed and integrated into MSTGCN to generate a new model called CNN-MSTGCN. …”
Get full text

Deep Learning Model for Feature Extraction and Anomaly Recognition in High-Dimensional Energy Metering Data by Huakun Que, Zetao Jiang, Zhifeng Zhou, Yongsheng He, Xin Liu

“…Methods: High-dimensional metering data from a city energy provider is processed using a Convolutional Autoencoder (CAE) to extract deep features and reduce dimensionality. These features are then fed into a Cascaded Long Short-Term Memory (CLSTM) network, which identifies anomalous patterns in the data. …”
Get full text

Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy by Jing Zhang, Lulu Cheng, Shan Jiang, Duosheng Zhu

Get full text

Analysis of Disease-Induced Changes in Human Locomotor Patterns Through the Co-Joint Synergistic Attention Algorithm by Jingyao Chen, Chen Wang, Zeng-Guang Hou, Pingye Deng, Liang Peng, Pu Zhang, Ningcun Xu

“…Objective: Aiming to quantify and analyze disease-induced alterations in human movement, we explored the co-joint synergy patterns in locomotion through a vision-based co-joint synergistic attention algorithm. …”
Get full text

Visualizing Relaxation in Wearables: Multi-Domain Feature Fusion of HRV Using Fuzzy Recurrence Plots by Puneet Arya, Mandeep Singh, Mandeep Singh

“…Unlike ECGs’ linear traces, FRPs are two-dimensional images that reveal distinctive textural patterns corresponding to autonomic changes. These visually rich patterns make it easier for even non-experts with minimal training to track changes in relaxation states. …”
Get full text

Hybrid Deep Learning Architecture with Adaptive Feature Fusion for Multi-Stage Alzheimer’s Disease Classification by Ahmad Muhammad, Qi Jin, Osman Elwasila, Yonis Gulzar

“…Unlike static fusion methods, our adaptive feature fusion layer employs an attention mechanism to dynamically integrate ResNet50’s localized structural features and vision transformer (ViT) global connectivity patterns, significantly enhancing stage-specific Alzheimer’s disease classification accuracy. …”
Get full text

Identifying hotspots and classifying the spatial distribution pattern of karst collapse pillars with Moran’s index in coal mine by Junsheng Yan, Junsheng Yan, Junsheng Yan, Zaibin Liu, Zaibin Liu, Zaibin Liu, Zaibin Liu, Hui Yang, Hui Yang, Hui Yang, Lin An, Lin An, Lin An, Wei Li, Tiantian Wang, Qian Xie, Qian Xie, Qian Xie, Chenguang Liu, Chenguang Liu, Chenguang Liu, Chenguang Liu

“…The method integrates morphological feature analysis of KCPs with a combined weighting scheme using the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM). …”
Get full text

Early Breast Cancer Prediction Using Thermal Images and Hybrid Feature Extraction-Based System by Doaa Youssef, Hanan Atef, Shaimaa Gamal, Jala El-Azab, Tawfik Ismail

“…This valuable information is encoded in the spatial and local intensity variations of acquired breast images, revealing hidden patterns. This article introduces a novel hybrid feature extraction approach that combines traditional and deep learning techniques to improve the prediction of breast cancer. …”
Get full text

UAV rice panicle blast detection based on enhanced feature representation and optimized attention mechanism by Shaodan Lin, Deyao Huang, Libin Wu, Zuxin Cheng, Dapeng Ye, Haiyong Weng

“…This design aims to enhance feature extraction and focus on critical image regions, addressing the challenges of detecting small and complex disease patterns in UAV-captured imagery. …”
Get full text

Identifying comorbidity patterns of mental health disorders in community-dwelling older adults: a cluster analysis by Joshua Tobin, Michaela Black, James Ng, Debbie Rankin, Jonathan Wallace, Catherine Hughes, Leane Hoey, Adrian Moore, Jinling Wang, Geraldine Horigan, Paul Carlin, Helene McNulty, Anne M. Molloy, Mimi Zhang

“…Abstract As global life expectancy increases, understanding mental health patterns and their associated risk factors in older adults becomes increasingly critical. …”
Get full text

Patterns of changing surface climate variability from the Last Glacial Maximum to present in transient model simulations by E. Ziegler, E. Ziegler, N. Weitzel, J.-P. Baudouin, M.-L. Kapsch, U. Mikolajewicz, L. Gregoire, R. Ivanovic, P. J. Valdes, C. Wirths, K. Rehfeld, K. Rehfeld

“…During the LGM and Holocene, they further reveal significant differences, as most simulations feature larger temperature variance during the LGM than the Holocene, in line with results from reconstructions.…”
Get full text

Schizo-Net: A <italic>novel</italic> Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning on Electroencephalogram-Based Brain Connectivity Indices by Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo

Get full text

ANOMALIES ON EEG IN PATIENTS WITH COGNITIVE EPILEPTIFORM DISINTEGRATION AND EPILEPTIC ENCEPHALOPATHIES, ASSOCIATED WITH С BENIGN EPILEPTIFORM PATTERNS OF CHILDHOOD by M. B. Mironov

“…On background of review and discussion of current scientific literature è own data the article presents the main clinical characteristics and anomalies on EEG in patients with cognitive epileptiform disintegration and epileptic encephalopathies, associated with ñ benign epileptiform patterns of childhood. The author describes in detail EEGpatterns — continuous spike and wave activity during sleep and benign epileptiform patterns of childhood, the role of these patterns and their special features in different syndromes of cognitive epileptiform disintegration. …”
Get full text

Interpretable Identification of Dynamic Adaptive Streaming over HTTP (DASH) Flows Based on Feature Engineering by Arkadiusz Biernacki

“…Our methodology involves feature generation, filtering, and clustering. The clustering used the most significant features to group similar traffic patterns. …”
Get full text

Innovative deep learning classifiers for breast cancer detection through hybrid feature extraction techniques by S. Vijayalakshmi, Binay Kumar Pandey, Digvijay Pandey, Mesfin Esayas Lelisho

“…These features are input into a 2D BiLSTM-CNN model designed to learn spatial and sequential patterns in mammogram images. …”
Get full text

Distribution of local curvature values as a structural feature for off-line handwritten signature verification by V. V. Starovoitov, U. Akhundjanov

“…When verifying a signature with N authentic signatures of the same person, N(N-1)/2 patterns of the proximity of pairs of genuine signatures and N images of pairs of proximity of the analyzed signature with genuine signatures are presented in the feature space. …”
Get full text

Optimized Time Series Feature Selection for Manufacturing AI: Reducing Complexity and Improving Classification Accuracy by Jaeseok Jang, Chanyoung Jung, Hail Jung

“…To address this, we propose two time series feature selection strategies. First, we extract meaningful variables by analyzing the time series patterns of non-defective and defective products. …”
Get full text

Surprise as a Chronotopic Feature of the World in the Poem by F.I. Tyutchev Exists in the Autumnal Growing... by Anastasia A. Aksyonova

Get full text

Enhancing DDoS Attack Classification through SDN and Machine Learning: A Feature Ranking Analysis by Aymen AlAwadi, Kawthar Rasoul ALesawi

“…Machine learning (ML) offers a promising way for early DDoS attack detection due to its ability to analyze large datasets and identify patterns. However, adding too many features to the ML might reduce its effectiveness in identifying the attacks provided by central network paradigms such as the Software-Defined Network (SDN). …”
Get full text